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66 results (View BibTeX file of all listed publications)

2010

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Markerless tracking of Dynamic 3D Scans of Faces

Walder, C., Breidt, M., Bülthoff, H., Schölkopf, B., Curio, C.

In Dynamic Faces: Insights from Experiments and Computation, pages: 255-276, (Editors: Curio, C., Bülthoff, H. H. and Giese, M. A.), MIT Press, Cambridge, MA, USA, December 2010 (inbook)

ei

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2010

ei Walder, C., Breidt, M., Bülthoff, H., Schölkopf, B., Curio, C. Markerless tracking of Dynamic 3D Scans of Faces In Dynamic Faces: Insights from Experiments and Computation, pages: 255-276, (Editors: Curio, C., Bülthoff, H. H. and Giese, M. A.), MIT Press, Cambridge, MA, USA, December 2010 (inbook)

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Policy Gradient Methods

Peters, J., Bagnell, J.

In Encyclopedia of Machine Learning, pages: 774-776, (Editors: Sammut, C. and Webb, G. I.), Springer, Berlin, Germany, December 2010 (inbook)

ei

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ei Peters, J., Bagnell, J. Policy Gradient Methods In Encyclopedia of Machine Learning, pages: 774-776, (Editors: Sammut, C. and Webb, G. I.), Springer, Berlin, Germany, December 2010 (inbook)

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Bayesian Inference and Experimental Design for Large Generalised Linear Models

Nickisch, H.

Biologische Kybernetik, Technische Universität Berlin, Berlin, Germany, September 2010 (phdthesis)

ei

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ei Nickisch, H. Bayesian Inference and Experimental Design for Large Generalised Linear Models Biologische Kybernetik, Technische Universität Berlin, Berlin, Germany, September 2010 (phdthesis)

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Inferring High-Dimensional Causal Relations using Free Probability Theory

Zscheischler, J.

Humboldt Universität Berlin, Germany, August 2010 (diplomathesis)

ei

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ei Zscheischler, J. Inferring High-Dimensional Causal Relations using Free Probability Theory Humboldt Universität Berlin, Germany, August 2010 (diplomathesis)

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Semi-supervised Subspace Learning and Application to Human Functional Magnetic Brain Resonance Imaging Data

Shelton, J.

Biologische Kybernetik, Eberhard Karls Universität, Tübingen, Germany, July 2010 (diplomathesis)

ei

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ei Shelton, J. Semi-supervised Subspace Learning and Application to Human Functional Magnetic Brain Resonance Imaging Data Biologische Kybernetik, Eberhard Karls Universität, Tübingen, Germany, July 2010 (diplomathesis)

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Quantitative Evaluation of MR-based Attenuation Correction for Positron Emission Tomography (PET)

Mantlik, F.

Biologische Kybernetik, Universität Mannheim, Germany, March 2010 (diplomathesis)

ei

[BibTex]

ei Mantlik, F. Quantitative Evaluation of MR-based Attenuation Correction for Positron Emission Tomography (PET) Biologische Kybernetik, Universität Mannheim, Germany, March 2010 (diplomathesis)

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JMLR Workshop and Conference Proceedings: Volume 6

Guyon, I., Janzing, D., Schölkopf, B.

pages: 288, MIT Press, Cambridge, MA, USA, Causality: Objectives and Assessment (NIPS Workshop) , February 2010 (proceedings)

ei

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ei Guyon, I., Janzing, D., Schölkopf, B. JMLR Workshop and Conference Proceedings: Volume 6 pages: 288, MIT Press, Cambridge, MA, USA, Causality: Objectives and Assessment (NIPS Workshop) , February 2010 (proceedings)

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Learning Continuous Grasp Affordances by Sensorimotor Exploration

Detry, R., Baseski, E., Popovic, M., Touati, Y., Krüger, N., Kroemer, O., Peters, J., Piater, J.

In From Motor Learning to Interaction Learning in Robots, pages: 451-465, Studies in Computational Intelligence ; 264, (Editors: Sigaud, O. and Peters, J.), Springer, Berlin, Germany, January 2010 (inbook)

Abstract
We develop means of learning and representing object grasp affordances probabilistically. By grasp affordance, we refer to an entity that is able to assess whether a given relative object-gripper configuration will yield a stable grasp. These affordances are represented with grasp densities, continuous probability density functions defined on the space of 3D positions and orientations. Grasp densities are registered with a visual model of the object they characterize. They are exploited by aligning them to a target object using visual pose estimation. Grasp densities are refined through experience: A robot “plays” with an object by executing grasps drawn randomly for the object’s grasp density. The robot then uses the outcomes of these grasps to build a richer density through an importance sampling mechanism. Initial grasp densities, called hypothesis densities, are bootstrapped from grasps collected using a motion capture system, or from grasps generated from the visual model of the object. Refined densities, called empirical densities, represent affordances that have been confirmed through physical experience. The applicability of our method is demonstrated by producing empirical densities for two object with a real robot and its 3-finger hand. Hypothesis densities are created from visual cues and human demonstration.

ei

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ei Detry, R., Baseski, E., Popovic, M., Touati, Y., Krüger, N., Kroemer, O., Peters, J., Piater, J. Learning Continuous Grasp Affordances by Sensorimotor Exploration In From Motor Learning to Interaction Learning in Robots, pages: 451-465, Studies in Computational Intelligence ; 264, (Editors: Sigaud, O. and Peters, J.), Springer, Berlin, Germany, January 2010 (inbook)

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Imitation and Reinforcement Learning for Motor Primitives with Perceptual Coupling

Kober, J., Mohler, B., Peters, J.

In From Motor Learning to Interaction Learning in Robots, pages: 209-225, Studies in Computational Intelligence ; 264, (Editors: Sigaud, O. and Peters, J.), Springer, Berlin, Germany, January 2010 (inbook)

Abstract
Traditional motor primitive approaches deal largely with open-loop policies which can only deal with small perturbations. In this paper, we present a new type of motor primitive policies which serve as closed-loop policies together with an appropriate learning algorithm. Our new motor primitives are an augmented version version of the dynamical system-based motor primitives [Ijspeert et al(2002)Ijspeert, Nakanishi, and Schaal] that incorporates perceptual coupling to external variables. We show that these motor primitives can perform complex tasks such as Ball-in-a-Cup or Kendama task even with large variances in the initial conditions where a skilled human player would be challenged. We initialize the open-loop policies by imitation learning and the perceptual coupling with a handcrafted solution. We first improve the open-loop policies and subsequently the perceptual coupling using a novel reinforcement learning method which is particularly well-suited for dynamical system-based motor primitives.

ei

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ei Kober, J., Mohler, B., Peters, J. Imitation and Reinforcement Learning for Motor Primitives with Perceptual Coupling In From Motor Learning to Interaction Learning in Robots, pages: 209-225, Studies in Computational Intelligence ; 264, (Editors: Sigaud, O. and Peters, J.), Springer, Berlin, Germany, January 2010 (inbook)

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From Motor Learning to Interaction Learning in Robots

Sigaud, O., Peters, J.

In From Motor Learning to Interaction Learning in Robots, pages: 1-12, Studies in Computational Intelligence ; 264, (Editors: Sigaud, O. and Peters, J.), Springer, Berlin, Germany, January 2010 (inbook)

Abstract
The number of advanced robot systems has been increasing in recent years yielding a large variety of versatile designs with many degrees of freedom. These robots have the potential of being applicable in uncertain tasks outside wellstructured industrial settings. However, the complexity of both systems and tasks is often beyond the reach of classical robot programming methods. As a result, a more autonomous solution for robot task acquisition is needed where robots adaptively adjust their behaviour to the encountered situations and required tasks. Learning approaches pose one of the most appealing ways to achieve this goal. However, while learning approaches are of high importance for robotics, we cannot simply use off-the-shelf methods from the machine learning community as these usually do not scale into the domains of robotics due to excessive computational cost as well as a lack of scalability. Instead, domain appropriate approaches are needed. In this book, we focus on several core domains of robot learning. For accurate task execution, we need motor learning capabilities. For fast learning of the motor tasks, imitation learning offers the most promising approach. Self improvement requires reinforcement learning approaches that scale into the domain of complex robots. Finally, for efficient interaction of humans with robot systems, we will need a form of interaction learning. This chapter provides a general introduction to these issues and briefly presents the contributions of the subsequent chapters to the corresponding research topics.

ei

Web DOI [BibTex]

ei Sigaud, O., Peters, J. From Motor Learning to Interaction Learning in Robots In From Motor Learning to Interaction Learning in Robots, pages: 1-12, Studies in Computational Intelligence ; 264, (Editors: Sigaud, O. and Peters, J.), Springer, Berlin, Germany, January 2010 (inbook)

Web DOI [BibTex]

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Real-Time Local GP Model Learning

Nguyen-Tuong, D., Seeger, M., Peters, J.

In From Motor Learning to Interaction Learning in Robots, 264, pages: 193-207, Studies in Computational Intelligence, (Editors: Sigaud, O. and Peters, J.), Springer, Berlin, Germany, January 2010 (inbook)

Abstract
For many applications in robotics, accurate dynamics models are essential. However, in some applications, e.g., in model-based tracking control, precise dynamics models cannot be obtained analytically for sufficiently complex robot systems. In such cases, machine learning offers a promising alternative for approximating the robot dynamics using measured data. However, standard regression methods such as Gaussian process regression (GPR) suffer from high computational complexity which prevents their usage for large numbers of samples or online learning to date. In this paper, we propose an approximation to the standard GPR using local Gaussian processes models inspired by [Vijayakumar et al(2005)Vijayakumar, D’Souza, and Schaal, Snelson and Ghahramani(2007)]. Due to reduced computational cost, local Gaussian processes (LGP) can be applied for larger sample-sizes and online learning. Comparisons with other nonparametric regressions, e.g., standard GPR, support vector regression (SVR) and locally weighted proje ction regression (LWPR), show that LGP has high approximation accuracy while being sufficiently fast for real-time online learning.

ei

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ei Nguyen-Tuong, D., Seeger, M., Peters, J. Real-Time Local GP Model Learning In From Motor Learning to Interaction Learning in Robots, 264, pages: 193-207, Studies in Computational Intelligence, (Editors: Sigaud, O. and Peters, J.), Springer, Berlin, Germany, January 2010 (inbook)

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Finding Gene-Gene Interactions using Support Vector Machines

Rakitsch, B.

Eberhard Karls Universität Tübingen, Germany, 2010 (diplomathesis)

ei

[BibTex]

ei Rakitsch, B. Finding Gene-Gene Interactions using Support Vector Machines Eberhard Karls Universität Tübingen, Germany, 2010 (diplomathesis)

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Accurate Prediction of Protein-Coding Genes with Discriminative Learning Techniques

Schweikert, G.

Technische Universität Berlin, Germany, 2010 (phdthesis)

ei

[BibTex]

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Machine Learning Methods for Automatic Image Colorization

Charpiat, G., Bezrukov, I., Hofmann, M., Altun, Y., Schölkopf, B.

In Computational Photography: Methods and Applications, pages: 395-418, Digital Imaging and Computer Vision, (Editors: Lukac, R.), CRC Press, Boca Raton, FL, USA, 2010 (inbook)

Abstract
We aim to color greyscale images automatically, without any manual intervention. The color proposition could then be interactively corrected by user-provided color landmarks if necessary. Automatic colorization is nontrivial since there is usually no one-to-one correspondence between color and local texture. The contribution of our framework is that we deal directly with multimodality and estimate, for each pixel of the image to be colored, the probability distribution of all possible colors, instead of choosing the most probable color at the local level. We also predict the expected variation of color at each pixel, thus defining a non-uniform spatial coherency criterion. We then use graph cuts to maximize the probability of the whole colored image at the global level. We work in the L-a-b color space in order to approximate the human perception of distances between colors, and we use machine learning tools to extract as much information as possible from a dataset of colored examples. The resulting algorithm is fast, designed to be more robust to texture noise, and is above all able to deal with ambiguity, in contrary to previous approaches.

ei

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ei Charpiat, G., Bezrukov, I., Hofmann, M., Altun, Y., Schölkopf, B. Machine Learning Methods for Automatic Image Colorization In Computational Photography: Methods and Applications, pages: 395-418, Digital Imaging and Computer Vision, (Editors: Lukac, R.), CRC Press, Boca Raton, FL, USA, 2010 (inbook)

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Structural and Relational Data Mining for Systems Biology Applications

Georgii, E.

Eberhard Karls Universität Tübingen, Germany , 2010 (phdthesis)

ei

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ei Georgii, E. Structural and Relational Data Mining for Systems Biology Applications Eberhard Karls Universität Tübingen, Germany , 2010 (phdthesis)

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Population Coding in the Visual System: Statistical Methods and Theory

Macke, J.

Eberhard Karls Universität Tübingen, Germany, 2010 (phdthesis)

ei

[BibTex]

ei Macke, J. Population Coding in the Visual System: Statistical Methods and Theory Eberhard Karls Universität Tübingen, Germany, 2010 (phdthesis)

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Bayesian Methods for Neural Data Analysis

Gerwinn, S.

Eberhard Karls Universität Tübingen, Germany, 2010 (phdthesis)

ei

Web [BibTex]

ei Gerwinn, S. Bayesian Methods for Neural Data Analysis Eberhard Karls Universität Tübingen, Germany, 2010 (phdthesis)

Web [BibTex]

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Approaches Based on Support Vector Machine to Classification of Remote Sensing Data

Bruzzone, L., Persello, C.

In Handbook of Pattern Recognition and Computer Vision, pages: 329-352, (Editors: Chen, C.H.), ICP, London, UK, 2010 (inbook)

Abstract
This chapter presents an extensive and critical review on the use of kernel methods and in particular of support vector machines (SVMs) in the classification of remote-sensing (RS) data. The chapter recalls the mathematical formulation and the main theoretical concepts related to SVMs, and discusses the motivations at the basis of the use of SVMs in remote sensing. A review on the main applications of SVMs in classification of remote sensing is given, presenting a literature survey on the use of SVMs for the analysis of different kinds of RS images. In addition, the most recent methodological developments related to SVM-based classification techniques in RS are illustrated by focusing on semisupervised, domain adaptation, and context sensitive approaches. Finally, the most promising research directions on SVM in RS are identified and discussed.

ei

Web [BibTex]

ei Bruzzone, L., Persello, C. Approaches Based on Support Vector Machine to Classification of Remote Sensing Data In Handbook of Pattern Recognition and Computer Vision, pages: 329-352, (Editors: Chen, C.H.), ICP, London, UK, 2010 (inbook)

Web [BibTex]

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Clustering with Neighborhood Graphs

Maier, M.

Universität des Saarlandes, Saarbrücken, Germany, 2010 (phdthesis)

ei

Web [BibTex]

ei Maier, M. Clustering with Neighborhood Graphs Universität des Saarlandes, Saarbrücken, Germany, 2010 (phdthesis)

Web [BibTex]

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Detecting the mincut in sparse random graphs

Köhler, R.

Eberhard Karls Universität Tübingen, Germany, 2010 (diplomathesis)

ei

[BibTex]

ei Köhler, R. Detecting the mincut in sparse random graphs Eberhard Karls Universität Tübingen, Germany, 2010 (diplomathesis)

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A wider view on encoding and decoding in the visual brain-computer interface speller system

Martens, S.

Eberhard Karls Universität Tübingen, Germany, 2010 (phdthesis)

ei

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Nanohandling robot cells

Fatikow, Sergej, Wich, Thomas, Dahmen, Christian, Jasper, Daniel, Stolle, Christian, Eichhorn, Volkmar, Hagemann, Saskia, Weigel-Jech, Michael

In Handbook of Nanophysics: Nanomedicine and Nanorobotics, pages: 1-31, CRC Press, 2010 (incollection)

pi

[BibTex]

pi Fatikow, Sergej, Wich, Thomas, Dahmen, Christian, Jasper, Daniel, Stolle, Christian, Eichhorn, Volkmar, Hagemann, Saskia, Weigel-Jech, Michael Nanohandling robot cells In Handbook of Nanophysics: Nanomedicine and Nanorobotics, pages: 1-31, CRC Press, 2010 (incollection)

[BibTex]

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Goal-Oriented Control of Self-Organizing Behavior in Autonomous Robots

Martius, G.

Georg-August-Universität Göttingen, 2010 (phdthesis)

al

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Locally weighted regression for control

Ting, J., Vijayakumar, S., Schaal, S.

In Encyclopedia of Machine Learning, pages: 613-624, (Editors: Sammut, C.;Webb, G. I.), Springer, 2010, clmc (inbook)

Abstract
This is article addresses two topics: learning control and locally weighted regression.

am

link (url) [BibTex]

am Ting, J., Vijayakumar, S., Schaal, S. Locally weighted regression for control In Encyclopedia of Machine Learning, pages: 613-624, (Editors: Sammut, C.;Webb, G. I.), Springer, 2010, clmc (inbook)

link (url) [BibTex]

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Statics and dynamics of simple fluids on chemically patterned substrates

Dörfler, F.

Universität Stuttgart, Stuttgart, Germany, 2010 (phdthesis)

mms

link (url) [BibTex]

mms Dörfler, F. Statics and dynamics of simple fluids on chemically patterned substrates Universität Stuttgart, Stuttgart, Germany, 2010 (phdthesis)

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Physisorption in porous materials

Hirscher, M., Panella, B.

In Handbook of Hydrogen Storage, pages: 39-62, WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim, 2010 (incollection)

mms

[BibTex]

mms Hirscher, M., Panella, B. Physisorption in porous materials In Handbook of Hydrogen Storage, pages: 39-62, WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim, 2010 (incollection)

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Entnetzung verspannter Filme

Reindl, A.

Universität Stuttgart, Stuttgart, 2010 (mastersthesis)

mms

[BibTex]

mms Reindl, A. Entnetzung verspannter Filme Universität Stuttgart, Stuttgart, 2010 (mastersthesis)

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Advanced ferromagnetic nanostructures

Goll, D.

Universität Stuttgart, Stuttgart, 2010 (phdthesis)

mms

[BibTex]

mms Goll, D. Advanced ferromagnetic nanostructures Universität Stuttgart, Stuttgart, 2010 (phdthesis)

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Wasserstoff in funktionellen Dünnschichtsystemen

Honert, J.

Universität Stuttgart, Stuttgart, 2010 (mastersthesis)

mms

[BibTex]

mms Honert, J. Wasserstoff in funktionellen Dünnschichtsystemen Universität Stuttgart, Stuttgart, 2010 (mastersthesis)

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Adsorption technologies

Schmitz, B., Hirscher, M.

In Hydrogen and Fuel Cells, pages: 431-445, WILEY-VCH, Weinheim, 2010 (incollection)

mms

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mms Schmitz, B., Hirscher, M. Adsorption technologies In Hydrogen and Fuel Cells, pages: 431-445, WILEY-VCH, Weinheim, 2010 (incollection)

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Atomic-Force-Microscopy-Based Nanomanipulation Systems

Onal, C. D., Ozcan, O., Sitti, M.

In Handbook of Nanophysics: Nanomedicine and Nanorobotics, pages: 1-15, CRC Press, 2010 (incollection)

pi

[BibTex]

pi Onal, C. D., Ozcan, O., Sitti, M. Atomic-Force-Microscopy-Based Nanomanipulation Systems In Handbook of Nanophysics: Nanomedicine and Nanorobotics, pages: 1-15, CRC Press, 2010 (incollection)

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Taming the Beast: Guided Self-organization of Behavior in Autonomous Robots

Martius, G., Herrmann, J. M.

In From Animals to Animats 11, 6226, pages: 50-61, LNCS, Springer, 2010 (incollection)

al

link (url) DOI [BibTex]

al Martius, G., Herrmann, J. M. Taming the Beast: Guided Self-organization of Behavior in Autonomous Robots In From Animals to Animats 11, 6226, pages: 50-61, LNCS, Springer, 2010 (incollection)

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2003

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Learning Theory and Kernel Machines: 16th Annual Conference on Learning Theory and 7th Kernel Workshop (COLT/Kernel 2003), LNCS Vol. 2777

Schölkopf, B., Warmuth, M.

Proceedings of the 16th Annual Conference on Learning Theory and 7th Kernel Workshop (COLT/Kernel 2003), COLT/Kernel 2003, pages: 746, Springer, Berlin, Germany, 16th Annual Conference on Learning Theory and 7th Kernel Workshop, November 2003, Lecture Notes in Computer Science ; 2777 (proceedings)

ei

DOI [BibTex]

2003

ei Schölkopf, B., Warmuth, M. Learning Theory and Kernel Machines: 16th Annual Conference on Learning Theory and 7th Kernel Workshop (COLT/Kernel 2003), LNCS Vol. 2777 Proceedings of the 16th Annual Conference on Learning Theory and 7th Kernel Workshop (COLT/Kernel 2003), COLT/Kernel 2003, pages: 746, Springer, Berlin, Germany, 16th Annual Conference on Learning Theory and 7th Kernel Workshop, November 2003, Lecture Notes in Computer Science ; 2777 (proceedings)

DOI [BibTex]

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Real-Time Face Detection

Kienzle, W.

Biologische Kybernetik, Eberhard-Karls-Universitaet Tuebingen, Tuebingen, Germany, October 2003 (diplomathesis)

ei

[BibTex]

ei Kienzle, W. Real-Time Face Detection Biologische Kybernetik, Eberhard-Karls-Universitaet Tuebingen, Tuebingen, Germany, October 2003 (diplomathesis)

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Extension of the nu-SVM range for classification

Perez-Cruz, F., Weston, J., Herrmann, D., Schölkopf, B.

In Advances in Learning Theory: Methods, Models and Applications, NATO Science Series III: Computer and Systems Sciences, Vol. 190, 190, pages: 179-196, NATO Science Series III: Computer and Systems Sciences, (Editors: J Suykens and G Horvath and S Basu and C Micchelli and J Vandewalle), IOS Press, Amsterdam, 2003 (inbook)

ei

[BibTex]

ei Perez-Cruz, F., Weston, J., Herrmann, D., Schölkopf, B. Extension of the nu-SVM range for classification In Advances in Learning Theory: Methods, Models and Applications, NATO Science Series III: Computer and Systems Sciences, Vol. 190, 190, pages: 179-196, NATO Science Series III: Computer and Systems Sciences, (Editors: J Suykens and G Horvath and S Basu and C Micchelli and J Vandewalle), IOS Press, Amsterdam, 2003 (inbook)

[BibTex]

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m-Alternative Forced Choice—Improving the Efficiency of the Method of Constant Stimuli

Jäkel, F.

Biologische Kybernetik, Graduate School for Neural and Behavioural Sciences, Tübingen, 2003 (diplomathesis)

ei

[BibTex]

ei Jäkel, F. m-Alternative Forced Choice—Improving the Efficiency of the Method of Constant Stimuli Biologische Kybernetik, Graduate School for Neural and Behavioural Sciences, Tübingen, 2003 (diplomathesis)

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An Introduction to Support Vector Machines

Schölkopf, B.

In Recent Advances and Trends in Nonparametric Statistics , pages: 3-17, (Editors: MG Akritas and DN Politis), Elsevier, Amsterdam, The Netherlands, 2003 (inbook)

ei

Web DOI [BibTex]

ei Schölkopf, B. An Introduction to Support Vector Machines In Recent Advances and Trends in Nonparametric Statistics , pages: 3-17, (Editors: MG Akritas and DN Politis), Elsevier, Amsterdam, The Netherlands, 2003 (inbook)

Web DOI [BibTex]

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Statistical Learning and Kernel Methods in Bioinformatics

Schölkopf, B., Guyon, I., Weston, J.

In Artificial Intelligence and Heuristic Methods in Bioinformatics, 183, pages: 1-21, 3, (Editors: P Frasconi und R Shamir), IOS Press, Amsterdam, The Netherlands, 2003 (inbook)

ei

[BibTex]

ei Schölkopf, B., Guyon, I., Weston, J. Statistical Learning and Kernel Methods in Bioinformatics In Artificial Intelligence and Heuristic Methods in Bioinformatics, 183, pages: 1-21, 3, (Editors: P Frasconi und R Shamir), IOS Press, Amsterdam, The Netherlands, 2003 (inbook)

[BibTex]

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A Short Introduction to Learning with Kernels

Schölkopf, B., Smola, A.

In Proceedings of the Machine Learning Summer School, Lecture Notes in Artificial Intelligence, Vol. 2600, pages: 41-64, LNAI 2600, (Editors: S Mendelson and AJ Smola), Springer, Berlin, Heidelberg, Germany, 2003 (inbook)

ei

[BibTex]

ei Schölkopf, B., Smola, A. A Short Introduction to Learning with Kernels In Proceedings of the Machine Learning Summer School, Lecture Notes in Artificial Intelligence, Vol. 2600, pages: 41-64, LNAI 2600, (Editors: S Mendelson and AJ Smola), Springer, Berlin, Heidelberg, Germany, 2003 (inbook)

[BibTex]

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Bayesian Kernel Methods

Smola, A., Schölkopf, B.

In Advanced Lectures on Machine Learning, Machine Learning Summer School 2002, Lecture Notes in Computer Science, Vol. 2600, LNAI 2600, pages: 65-117, 0, (Editors: S Mendelson and AJ Smola), Springer, Berlin, Germany, 2003 (inbook)

ei

DOI [BibTex]

ei Smola, A., Schölkopf, B. Bayesian Kernel Methods In Advanced Lectures on Machine Learning, Machine Learning Summer School 2002, Lecture Notes in Computer Science, Vol. 2600, LNAI 2600, pages: 65-117, 0, (Editors: S Mendelson and AJ Smola), Springer, Berlin, Germany, 2003 (inbook)

DOI [BibTex]

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Stability of ensembles of kernel machines

Elisseeff, A., Pontil, M.

In 190, pages: 111-124, NATO Science Series III: Computer and Systems Science, (Editors: Suykens, J., G. Horvath, S. Basu, C. Micchelli and J. Vandewalle), IOS press, Netherlands, 2003 (inbook)

ei

[BibTex]

ei Elisseeff, A., Pontil, M. Stability of ensembles of kernel machines In 190, pages: 111-124, NATO Science Series III: Computer and Systems Science, (Editors: Suykens, J., G. Horvath, S. Basu, C. Micchelli and J. Vandewalle), IOS press, Netherlands, 2003 (inbook)

[BibTex]

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Investigation of the Initial Oxidation of Surfaces of Quasicrystals by High-Resolution RBS and ERDA

Plachke, D., Khellaf, A., Kurth, M., Szökefalvi-Nagy, A., Carstanjen, H. D.

In Quasicrystals: Structure and Physical Properties, pages: 598-614, Wiley-VCH GmbH & Co. KGaA, Weinheim, 2003 (incollection)

mms

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mms Plachke, D., Khellaf, A., Kurth, M., Szökefalvi-Nagy, A., Carstanjen, H. D. Investigation of the Initial Oxidation of Surfaces of Quasicrystals by High-Resolution RBS and ERDA In Quasicrystals: Structure and Physical Properties, pages: 598-614, Wiley-VCH GmbH & Co. KGaA, Weinheim, 2003 (incollection)

[BibTex]